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Compact closed categories provide a foundational formalism for a variety of important domains, including quantum computation. These categories have a natural visualisation as a form of graphs. We present a formalism for equational reasoning…

Symbolic Computation · Computer Science 2009-02-04 Lucas Dixon , Ross Duncan

We relate the computational complexity of finite strings to universal representations of their underlying symmetries. First, Boolean functions are classified using the universal covering topologies of the circuits which enumerate them. A…

Information Theory · Computer Science 2011-09-20 John Scoville

The relationship between quantum physics and discrete mathematics is reviewed in this article. The Boolean functions unitary representation is considered. The relationship between Zhegalkin polynomial, which defines the algebraic normal…

Quantum Physics · Physics 2019-06-18 Yu. I. Bogdanov , N. A. Bogdanova , D. V. Fastovets , V. F. Lukichev

Capitalizing on previous encodings and formal developments about nominal calculi and type systems, we propose a weak Higher-Order Abstract Syntax formalization of the type language of pure System F<: within Coq, a proof assistant based on…

Logic in Computer Science · Computer Science 2013-04-01 Alberto Ciaffaglione , Ivan Scagnetto

Symbolic integration deals with the evaluation of integrals in closed form. We present an overview of Risch's algorithm including recent developments. The algorithms discussed are suited for both indefinite and definite integration. They…

Symbolic Computation · Computer Science 2013-05-08 C. G. Raab

The article explores the arithmetic of multiplication as a model of many valued projective logic. It is demonstrated that closed numerical intervals within this framework constitute Heyting algebras. The conditions for these algebras to be…

Logic · Mathematics 2024-06-04 Volodymyr Zhuravlov

Inspired by Solomonoffs theory of inductive inference, we propose a prior based on circuit complexity. There are several advantages to this approach. First, it relies on a complexity measure that does not depend on the choice of UTM. There…

Machine Learning · Computer Science 2023-06-27 Cole Wyeth , Carl Sturtivant

An important tool in the study of the complexity of Constraint Satisfaction Problems (CSPs) is the notion of a relational clone, which is the set of all relations expressible using primitive positive formulas over a particular set of base…

Computational Complexity · Computer Science 2013-10-25 Andrei A. Bulatov , Martin Dyer , Leslie Ann Goldberg , Mark Jerrum , Colin McQuillan

Probabilistic program analysis aims to quantify the probability that a given program satisfies a required property. It has many potential applications, from program understanding and debugging to computing program reliability, compiler…

Programming Languages · Computer Science 2017-09-08 Aleksandar S. Dimovski

String diagrams are an increasingly popular algebraic language for the analysis of graphical models of computations across different research fields. Whereas string diagrams have been thoroughly studied as semantic structures, much less…

Category Theory · Mathematics 2022-11-04 Paul Wilson , Fabio Zanasi

This paper advances the theoretical understanding of active learning label complexity for decision trees as binary classifiers. We make two main contributions. First, we provide the first analysis of the disagreement coefficient for…

Regular expressions are widely used in software. Various regular expression engines support different combinations of extensions to classical regular constructs such as Kleene star, concatenation, nondeterministic choice (union in terms of…

Formal Languages and Automata Theory · Computer Science 2023-09-27 Ian Erik Varatalu , Margus Veanes , Juhan-Peep Ernits

As dynamic and control systems become more complex, relying purely on numerical computations for systems analysis and design might become extremely expensive or totally infeasible. Computer algebra can act as an enabler for analysis and…

Systems and Control · Computer Science 2018-01-01 Masoud Abbaszadeh

Using semi-tensor product of matrices, the structures of several kinds of symmetric games are investigated via the linear representation of symmetric group in the structure vector of games as its representation space. First of all, the…

Computer Science and Game Theory · Computer Science 2017-03-09 Daizhan Cheng , Ting Liu

In this paper, we study the hardness of solving graph-structured linear systems with coefficients over a finite field $\mathbb{Z}_p$ and over a polynomial ring $\mathbb{F}[x_1,\ldots,x_t]$. We reduce solving general linear systems in…

Data Structures and Algorithms · Computer Science 2022-11-09 Jingbang Chen , Yu Gao , Yufan Huang , Richard Peng , Runze Wang

In symbolic computing, a major bottleneck is middle expression swell. Symbolic geometric computing based on invariant algebras can alleviate this difficulty. For example, the size of projective geometric computing based on bracket algebra…

Metric Geometry · Mathematics 2007-05-23 Hongbo Li

Boolean functions can be represented in many ways including logical forms, truth tables, and polynomials. Additionally, Boolean functions have different canonical representations such as minimal disjunctive normal forms. Other canonical…

Computational Complexity · Computer Science 2024-11-19 Elena Dimitrova , Brandilyn Stigler , Claus Kadelka , David Murrugarra

Description Logics (DLs) are used in knowledge-based systems to represent and reason about terminological knowledge of the application domain in a semantically well-defined manner. In this thesis, we establish a number of novel complexity…

Logic in Computer Science · Computer Science 2007-05-23 Stephan Tobies

Symbolic computation systems suffer from memory inefficiencies due to redundant storage of structurally identical subexpressions, commonly known as expression swell, which degrades performance in both classical computer algebra and emerging…

Programming Languages · Computer Science 2025-10-17 Bowen Zhu , Aayush Sabharwal , Songchen Tan , Yingbo Ma , Alan Edelman , Christopher Rackauckas

We introduce Boolformer, a Transformer-based model trained to perform end-to-end symbolic regression of Boolean functions. First, we show that it can predict compact formulas for complex functions not seen during training, given their full…

Machine Learning · Computer Science 2025-07-18 Stéphane d'Ascoli , Arthur Renard , Vassilis Papadopoulos , Samy Bengio , Josh Susskind , Emmanuel Abbé
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